The Association between Obstructive Sleep Apnea and ...

OSA AND NEUROCOGNITIVE PERFORMANCE

The Association between Obstructive Sleep Apnea and Neurocognitive Performance—The Apnea Positive Pressure Long-term Efficacy Study (APPLES) Stuart F. Quan, MD1,2; Cynthia S. Chan, BS3; William C. Dement, MD, PhD4; Alan Gevins, DSc3; James L. Goodwin, PhD1; Daniel J. Gottlieb, MD, MPH5; Sylvan Green, MD10; Christian Guilleminault, MD4; Max Hirshkowitz, PhD6; Pamela R. Hyde, MA4; Gary G. Kay, PhD7; Eileen B. Leary, RPSGT4; Deborah A. Nichols, MS4; Paula K. Schweitzer, PhD8; Richard D. Simon, MD9; James K. Walsh, PhD8; Clete A. Kushida, MD, PhD4 Arizona Respiratory Center, University of Arizona, Tucson, AZ; 2Division of Sleep Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; 3The San Francisco Brain Research Institute and SAM Technology, San Francisco, CA; 4Stanford University, Stanford, CA; 5Boston University School of Medicine, Boston, MA; 6Baylor College of Medicine and VA Medical Center, Houston, TX; 7Cogscreen, LLC, Washington, DC; 8St. Luke’s Hospital, Chesterfield, MO; 9St. Mary Medical Center, Walla Walla, WA; 10College of Public Health, University of Arizona, Tucson, AZ 1

Study Objectives: To determine associations between obstructive sleep apnea (OSA) and neurocognitive performance in a large cohort of adults. Study Design: Cross-sectional analyses of polysomnographic and neurocognitive data from 1204 adult participants with a clinical diagnosis of obstructive sleep apnea (OSA) in the Apnea Positive Pressure Long-term Efficacy Study (APPLES), assessed at baseline before randomization to either continuous positive airway pressure (CPAP) or sham CPAP. Measurements: Sleep and respiratory indices obtained by laboratory polysomnography and several measures of neurocognitive performance. Results: Weak correlations were found for both the apnea hypopnea index (AHI) and several indices of oxygen desaturation and neurocognitive performance in unadjusted analyses. After adjustment for level of education, ethnicity, and gender, there was no association between the AHI and neurocognitive performance. However, severity of oxygen desaturation was weakly associated with worse neurocognitive performance on some measures of intelligence, attention, and processing speed. Conclusions: The impact of OSA on neurocognitive performance is small for many individuals with this condition and is most related to the severity of hypoxemia. Keywords: Obstructive sleep apnea, neurocognition, epidemiology, sleep, oxygen desaturation Citation: Quan SF; Chan CS; Dement WC; Gevins A; Goodwin JL; Gottlieb DJ; Green S; Guilleminault C; Hirshkowitz M; Hype PR; Kay GG; Leary EB; Nichols DA; Schweitzer PK; Simon RD; Walsh JK; Kushida CA. The association between obstructive sleep apnea and neurocognitive performance—the Apnea Positive Pressure Long-term Efficacy Study (APPLES). SLEEP 2011;34(3):303-314.

INTRODUCTION The obstructive sleep apnea syndrome (OSA) is a potentially life-threatening sleep related breathing disorder estimated in 1993 to affect 4% of men and 2% of women in the United States between the ages of 30 and 60 years.1 The prevalence appears to be increasing with trends towards higher rates of obesity.2 Recent data from several large observational cohort studies provide strong evidence that untreated OSA is an independent risk factor for incident hypertension, cardiovascular disease and stroke, as well as higher all-cause mortality.3-8 Somewhat less attention has been paid to the relationship between OSA and neurocognitive abilities, especially in the domains of attention, memory and executive function. A number of studies primarily in clinical populations have examined the relationship between OSA and neurocognitive function.9,10 However, results are inconsistent. Various studies have observed that OSA is associated with impaired cognition.11-16 Some report executive and psychomotor deficits,

attention and memory problems, and impaired vigilance,14 and motor and perceptual-organization ability deficits.12 The mechanism responsible for these impairments also may differ according to the neurocognitive domain tested. In some studies, memory deficits are associated with the apnea hypopnea index, whereas frontal lobe-related dysfunction correlated best with the severity of OSA associated hypoxemia.15,16 In addition, neurocognitive abilities in persons with OSA may be variably affected for a variety of reasons including differential sensitivity to sleep disturbance. A meta-analytic review suggests that OSA has a moderate to severe impact on vigilance, motor coordination, and executive functions, while there is little effect on intelligence, verbal, and visual-perceptual abilities.17 Whether mild OSA impacts neurocognition also is unclear. Although there are reports of impairment in vigilance and working memory18 as well as psychomotor function19 in persons with mild OSA, not all studies have observed similar findings.20 Although the preponderance of evidence indicates reduced neurocognitive performance does occur in persons with OSA, there are inconsistencies in the type and degree of impairment, and the underlying mechanism responsible. These discrepancies could be due to the size and type of population studied, sensitivity of the neurocognitive tests employed, and the definitions used to characterize OSA.21 There have been few large studies performed, and their neurocognitive assessments were limited.22,23 A large study using a variety of neurocognitive outcomes with enrollment of a study population having OSA

A commentary on this article appears in this issue on page 249. Submitted for publication May, 2010 Submitted in final revised form July, 2010 Accepted for publication August, 2010 Address correspondence to: Stuart F. Quan, MD, Division of Sleep Medicine, Harvard Medical School, 401 Park Dr., 2nd Floor East, Boston, MA 02215; Tel: (617) 998-8842; Fax: (617) 998-8823; E-mail: squan@arc.

arizona.edu

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Obstructive Sleep Apnea and Neurocognitive Performance—Quan et al

ford University, Stanford, CA; University of Arizona, Tucson, AZ; Brigham and Women’s Hospital, Boston, MA; St. Luke’s Hospital, Chesterfield, MO; and St. Mary Medical Total Men Women Center, Walla Walla, WA), subjects were recruited into the Mean (SD) Mean (SD) Mean (SD) study primarily from patients scheduled into a regular sleep Intelligence3 clinic for evaluation of possible OSA and from local adverWASI Full 112.0 (13.2) 112.82 (12.9) 110.7 (13.5) tising. Although recruitment source was not tracked, it is WASI Verbal 109.8 (13.4) 109.9 (13.4) 109.7 (13.5) estimated that initial contact with ~70% of the subjects ocWASI Vocabulary 55.9 (9.7) 56.1 (9.7) 55.7 (9.7) curred as a result of advertisement. Symptoms indicative of WASI Similarities 56.0 (7.9) 55.9 (7.9) 56.0 (8.0) OSA were used as pre-screening questions. Initially, a clinical evaluation was conducted which included administerWASI Performance 111.5 (13.3) 112.92 (13.2) 109.1 (13.2) ing informed consent, screening questionnaires, history and WASI Block Design 54.0 (9.0) 55.52 (7.7) 52.3 (9.0) physical examination and a medical assessment by a study WASI Matrix physician. Inclusion criteria were a clinical diagnosis of Reasoning 59.2 (8.4) 59.61 (8.4) 58.5 (8.3) OSA, as defined by American Academy of Sleep Medicine Primary Neurocognitive Outcomes3 (AASM) criteria,25 an apnea hypopnea index (AHI) ≥ 10 by SWMT 0.000 (0.28) -0.01 (0.23) 0.02 (0.28) polysomnography (PSG), and age ≥ 18 years. Exclusion criPathfinder 24.43 (8.50) 24.4 (8.89) 24.5 (5.74) teria have been published previously,24 the most important 2 BSRT 49.98 (9.14) 48.72 (9.12) 52.21 (8.74) of which were non-enrollment of those with previous CPAP Secondary Neurocognitive Outcomes3 use, oxygen desaturation on PSG < 75% for > 10% of the PVT Median 251.83 (38.86) 245.542 (38.60) 262.92 (36.82) recording time, history of a motor vehicle accident related PVT Mean 465.97 (329.91) 448.522 (36.83) 500.31 (360.22) to sleepiness, presence of a number of chronic medical conPASAT 154.97 (42.73) 159.322 (42.38) 147.34 (42.32) ditions, and use of various medications with the potential Mood3 to affect sleep or neurocognitive function. Furthermore, poHAM-D 4.43 (4.13) 3.802 (3.72) 5.54 (4.57) tential subjects who scored ≤ 26 on the Mini Mental State Examination (MMSE) were generally excluded, although in Sleepiness3 some cases, subjects with lower scores were allowed to parESS 10.15 (4.35) 9.941 (4.23) 10.52 (4.52) ticipate at the discretion of the site investigator (1.2%, Table SSS 2.91 (0.98) 2.812 (0.96) 3.09 (1.00) 1). Subjects subsequently returned approximately 2-4 weeks 3 MMSE N (%) N (%) N (%) later for a 24-h sleep laboratory visit, where a diagnostic 5 5 26 14 (1.2) 9 (1.2) 5 (1.1) PSG was performed to confirm the presence of OSA (vide 27 79 (6.6) 53 (6.9) 26 (6.0) infra) followed by a day of neurocognitive and maintenance 28 169 (14.0) 114 (14.8) 55 (12.6) of wakefulness testing. Approximately 10-14 days later, the 29 401 (33.3) 263 (34.2) 138 (31.7) subject’s AHI was received from the central PSG Scoring 30 540 (44.9) 330 (42.9) 210 (48.3) Center. Only those subjects with an AHI ≥ 10 events/h were considered to have OSA, and were randomized to continue 1 P < 0.05 Men vs. Women; 2P < 0.01 Men vs. Women; 3See text for abbreviations; participation in the APPLES study. However, for the pres4 N for each variable ranges from 1143 (SWMT) to 1204 (ESS); 51 Subject with ent analysis, data from both randomized and participants a MMSE score = 25 included. not randomized on the basis of PSG exclusion criteria were included, provided that they had a baseline polysomnogram. severity spanning the spectrum from mild to severe would be Only data obtained during this baseline visit was used in the informative in addressing some of these inconsistencies. current analysis. Information regarding subsequent APPLES The Apnea Positive Pressure Long-term Efficacy Study data collection is available in a previous publication.24 (APPLES) is a randomized, double-blinded, sham-controlled, multi-center trial of continuous positive airway pressure (CPAP) Polysomnography therapy, designed to determine whether CPAP improves neuThe PSG montage included monitoring of the electroencephrocognitive function over a 6-month test period. The present alogram (EEG, C3-M2, C4-M1, O2-M1 and O1-M2), electroocustudy is an analysis of the relationship between a variety of neulogram (EOG, ROC-M1, LOC-M2), submentalis and anterior rocognitive measures at the baseline visit (pre-CPAP) and setibialis electromyograms (EMG), heart rate by 2-lead electroverity of OSA in 1204 APPLES participants. We hypothesized cardiogram, snoring intensity (anterior neck microphone), nasal that impairment on several neurocognitive domains would be pressure (nasal cannula), nasal/oral thermistor, thoracic and abassociated with severity of OSA and that lower performance dominal movement (piezo bands), and oxygen saturation (pulse would be related to hypoxemia. oximetry). All PSGs were electronically transmitted to the Data Coordinating Center. Sleep and wakefulness were scored using MATERIALS AND METHODS Rechtschaffen and Kales criteria.26 Apneas and hypopneas were scored using AASM (1999) criteria.27 Briefly, an apnea was deStudy Population and Protocol fined by a clear decrease (> 90%) from baseline in the ampliA detailed description of the APPLES protocol has been tude of the nasal pressure signal lasting ≥ 10 sec. Hypopneas previously published.24 Briefly, at all 5 APPLES sites (Stanwere identified if there was a clear decrease (> 50% but ≤ 90%) Table 1—Baseline neurocognitive, mood, mental status, and sleepiness data for all participants4 and stratified by gender

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from baseline in the amplitude of the nasal pressure signal, or if there was a clear amplitude reduction of the nasal pressure signal that did not reach the above criterion but it was associated with either an oxygen desaturation > 3% or an arousal, and the event duration was ≥ 10 seconds. Obstructive events were identified by persistence of chest or abdominal respiratory effort during flow cessation. Central events were noted if no displacement occurred on either the chest or abdominal channels. The apnea hypopnea index (AHI) was calculated as the sum of all apneic and hypopneic events divided by the hours of total sleep time (TST). The central apnea index, arousal index, periodic limb movement index, and desaturation index (based on 3% desaturation from baseline) were computed similarly.

variable selected for analysis. The range for this variable is a minimum score of 0 up to a maximum score of 72. Sustained Working Memory Test (SWMT): The SWMT measures working memory which is thought to be a frontal/ executive function. The test combines an N-back working memory task with simultaneous electroencephalographic (EEG) recording. The task requires the subject to sit in front of a computer monitor and maintain fixation on the middle of the computer screen. Every few seconds a simple visual stimulus appears briefly at a random screen location. Subjects are required to compare the spatial position of the initial stimulus with the position of the stimulus that occurred on a previous trial, and to press one button if the spatial position was the same as that on the previous trial, or a second button if it differed. In order to vary task difficulty, the comparison trial varies from the prior trial (1-back) to 2 trials prior (2-back). Behavioral and EEG (both background EEG and event-related potential) parameters are extracted from the resulting data. The behavioral data that are acquired provide evidence about any changes in the overt performance abilities of the subject, whereas the task-related EEG measures provide evidence about how the brain responds to changes in task difficulty. These measures are combined to yield a composite score indicating the degree of change from pretreatment baseline. The test has been shown to be sensitive to changes in alertness induced by sleep deprivation.32 For APPLES, these data were provided as 3 sub-indices: Behavioral, Activation, and Alertness, that were combined to yield an Overall Index. The Overall Index for the mid-day administration was selected as the primary outcome variable. A positive score indicates improvement from pre-treatment baseline, while a negative score indicates worsening. Due to the fact that the SWMT is formulated as a change from baseline score, there is no baseline variable to analyze for the Overall Index. Instead, a distinct variable measuring diurnal variation between the three baseline administrations was utilized for the purpose of this manuscript.

Neurocognitive Testing Primary outcomes

All neurocognitive testing was performed in the same predefined order for all subjects on the day after their diagnostic PSG. The testing was preceded by 2 training sessions.24 Typically, the first occurred several days or weeks before the diagnostic PSG, and the second on the night before the PSG. The neurocognitive testing schedule is provided in Appendix 1. There were 3 prespecified primary neurocognitive outcomes, each representing 1 of 3 different neurocognitive domains: (1) attention and psychomotor function, (2) learning and memory, and (3) executive and frontal-lobe function. The primary neurocognitive outcomes were selected as a result of recommendations made by the study’s neurocognitive function consulting team.24 A brief description of each of these tests follows. Pathfinder Number Test (Pathfinder): The Pathfinder Test assesses attention and psychomotor function, requiring the subject to scan, locate, and connect numbers in sequence. The Pathfinder Test is the computer analogue of the Trail Making Test Part A and is part of the APPLES edition of the CogScreen test battery designed to assess specific neurocognitive changes associated with OSA following CPAP therapy.28 The participant is instructed to select consecutive numbers on a computer screen by tapping a light pen to numbers which appear in boxes in the quadrants of the screen. In addition to selecting the next number as quickly as possible, the participant is instructed to tap the center of each box to provide a measure of psychomotor coordination. The variable selected for primary analyses was the total time required to complete the test. Performance on the Trail Making Test Part A has been reported to improve with treatment of OSA.29 The Cogscreen software is capable of one millisecond timing resolution. The ceiling for this variable is 60.00 seconds. Buschke Verbal Selective Reminding Test (BSRT): The BSRT is a multiple-trial, list-learning task that is a measure of verbal learning with short-term and long-term memory components.30 For APPLES, a series of 12 unrelated words were presented over 6 selective reminding trials, or until the subject was able to recall the entire list on three consecutive trials.31 Lastly, a delayed-recall trial was given with forewarning 30 min after the completion of the test. The BSRT has been used in OSA subjects to indicate a learning deficit in patients with moderate and severe OSA.16 The sum recall variable, or total number of correctly recalled words over the 6 trials, was the primary SLEEP, Vol. 34, No. 3, 2011

Secondary outcomes

In addition to the primary neurocognitive outcomes, other measures included in the APPLES test battery were exploratory neurobehavioral measures and sleepiness, fatigue, mood, quality of life, and sleep and health history assessments. These are shown in Appendix 2. Secondary outcome measures included in this analysis were the Wechsler Abbreviated Scale of Intelligence (WASI), Psychomotor Vigilance Test (PVT), Paced Auditory Serial Addition Test (PASAT), and the Epworth Sleepiness Scale (ESS). In addition, the Hamilton Rating Scale for Depression (HAM-D), ESS (when not assessed as an outcome measure), and the Stanford Sleepiness Scale (SSS) were used as covariates because of their potential to affect performance on the neurocognitive outcomes. Although there were a number of secondary outcomes included in the APPLES test battery, measures were selected for this analysis based on administration in previous studies and discussions among members of the study’s neurocognitive function consulting team. A brief description of these measures follows. Wechsler Abbreviated Scale of Intelligence (WASI): The Wechsler Adult Intelligence Scale (WAIS) is a standardized and validated instrument commonly used to assess adult 305


intelligence. For APPLES, we administered an abbreviated version of the WAIS, the Wechsler Abbreviated Scale of Intelligence (WASI).33 designed to provide a shorter, yet reliable intelligence measure for research settings. The WASI is standardized and linked to the WAIS-III. For this analysis, we report the Full Scale WASI IQ (WASI-Full), Verbal WASI IQ (WASI-Verbal) and Performance WASI IQ (WASI-Perf) as well as their respective components, Vocabulary WASI (WASI-Vocab), Similarities WASI (WASI-Simil), Block Design WASI (WASI-BD), and the Matrix Reasoning WASI (WASI-MATR). The WASI-Verbal is a measure of verbal comprehension. Its components are the WASI-Vocab (testing comprehension and expression of verbal vocabulary) and WASI-Simil (assessing verbal reasoning). The WASI-Perf is an assessment of perceptual organization. Its components are the WASI-BD (testing spatial perception, visual abstract processing, and problem solving) and the WASI-MATR (assessing nonverbal abstract problem solving, inductive reasoning, and spatial reasoning). The WASI-Full reflects the combined performance on both the WASI-Verbal and the WASI-Perf. The WASI uses age-based standard scores for composites, with a mean of 100 and standard deviation of 15; higher scores indicate better performance. Psychomotor Vigilance Test (PVT): The PVT is a simple reaction time test that measures sustained attention and psychomotor function.34 It is highly sensitive to sleepiness and yet has little practice effect.35 The test utilized the PVT-192 device which displays a stimulus (red light) intermittently (inter-stimulus interval 2000-10000 ms). As soon as the stimulus appears, the subject is required to press a button on the device with his/ her dominant hand, as quickly and as consistently as possible, to stop the reaction time counter, which counts time in milliseconds. For APPLES, a 10-min PVT was administered once in the morning and once in the afternoon. A number of outcomes can be derived from the PVT. For this analysis, the median reaction time for all correct responses (PVT Median) and the mean of the slowest 10% of reaction times (PVT Mean) for the first PVT administration are used. Paced Auditory Serial Addition Test (PASAT): The PASAT assesses auditory information processing speed and flexibility, as well as calculation ability.36 Subjects listen to a recording of spoken single numerical digits spaced every 2.4 sec (trial 1), every 2.0 sec (trial 2), every 1.6 sec (trial 3), or every 1.2 sec (trial 4). Their task is to add each new digit to the one immediately prior to it, and verbally respond with the sum. For APPLES, the 60-item version was utilized (60 possible sums per trial). The variable selected for analysis is the total number of correct sums for all trials. The minimum score is 0 and the maximum score is 240. Hamilton Rating Scale for Depression (HAM-D): The HAM-D is a validated 21-item clinician-administered assessment of the severity of depression.37 APPLES used a modified version of this test, the GRID Hamilton Rating Scale for Depression which was developed through a broad-based international consensus process to both simplify and standardize administration and scoring in clinical practice and research. In this scale, 17 items (e.g., depressed mood, suicide, work and anhedonia, retardation, agitation, gastrointestinal or general somatic symptoms, hypochondriasis, loss of insight or weight) SLEEP, Vol. 34, No. 3, 2011

are scored using either a 3- or 5-point scale based on intensity and frequency, and are summed to provide a single score. Epworth Sleepiness Scale (ESS): The ESS is a validated self-administered questionnaire that asks an individual to rate his or her probability of falling asleep on a scale of increasing probability from 0 to 3 in 8 different situations.38 The scores for the 8 questions are summed to obtain a single score from 0 to 24 that is indicative of self-reported sleep propensity. Stanford Sleepiness Scale (SSS): The SSS asks a person to rate current moment sleepiness on a scale of one to seven.39 Each numerical rating has an associated descriptor, for example a rating of 1 is described as “feeling active, vital, alert, or wide awake,” while a rating of 7 is described as “no longer fighting sleep, sleep onset soon; having dream-like thoughts.” For APPLES the SSS was administered at 10:00, 12:00, 14:00, and 16:00; the variable analyzed was the mean score from these 4 trials. Data Analysis Data from continuous and interval variables were reviewed to determine whether there were any that had extremely skewed distributions. As a consequence of this inspection, log transformation was performed to normalize the distribution of the following variables: PVT Median, PVT Mean, sleep latency, and % total sleep time with desaturation less than 85% (O2 Saturation < 85%). Subsequently, 60% of the cohort was randomly selected for further exploration of the data. Bivariate associations between neurocognitive measures, and demographic, sleep and respiratory variables were calculated using analysis of variance, Student’s unpaired t-test, Mann-Whitney U Test, and Pearson correlation coefficients as appropriate. Except for calculation of the mean data, no further analyses were performed for the SWMT because this measure was developed only for use as an indicator of change from baseline. For each of the other neurocognitive measures, multivariate models were constructed using analysis of covariance incorporating as independent variables only those that had significant bivariate associations with the dependent variable. Some of the sleep and respiratory variables were highly inter-correlated. In these cases, the single variable which had either the best bivariate association or resulted in the best adjusted r2 was used. After multivariate models were constructed using the 60% exploratory sample, the models then were validated using the remaining 40% of the sample. Final models displayed in the tables reflect results derived only from the 40% validation cohort. Data for continuous and interval variables are expressed as mean ± SD and for categorical variables as a percentage. P ≤ 0.05 was considered statistically significant. Analyses were performed using SPSS 17.0 (SPSS, Inc., Chicago, IL). RESULTS Table 2 shows the demographic data for all participants who had a baseline visit and those who were subsequently randomized stratified by gender. There were 1204 participants who had a baseline polysomnogram; 1098 were ultimately randomized. As expected, both cohorts were obese, and there was a greater proportion of men. In addition, approximately 75% of the participants were Caucasian and the majority were married. Importantly, most participants were relatively well educated, with 306


Table 2—Baseline demographics for all participants and subsequently randomized participants stratified by gender Total Mean (SD) or Count (%) Participant Enrollment Total Number of Participants Site Enrollment Stanford University (%) University of Arizona (%) St. Mary Medical Center (%) St. Luke’s Hospital (%) Brigham and Women’s Hospital (%) Demographic Data Age (y) BMI (kg/m2) Highest Grade Level (y) Ethnicity White (%) Native American (%) Asian Pacific Islander (%) Black (%) Hispanic (%) Other (%) Marital Status Married (%) Single (%) Divorced (%) Widowed (%) Smoking Current Smokers (%) Alcohol Use Consumption > 7 Servings/Week (%) Servings/Week Caffeine Use Consumption > 14 Servings/Week (%) Servings/Week Self Report Sleep Time Hours per Weeknight Hours per Weekend Night

Men Mean (SD) or Count (%)

Women Mean (SD) or Count (%)

769 (63.9)

435 (36.1)

303 (25.2) 346 (28.7) 117 (9.7) 193 (16.0) 245 (20.3)

188 (24.4) 232 (30.2) 74 (9.6) 132 (17.2) 143 (18.6)

115 (26.4) 114 (26.2) 43 (9.9) 61 (14.0) 102 (23.4)

50.7 (12.6) 32.0 (7.3) 15.5 (2.6)

50.3 (12.7) 31.3 (6.4)2 15.6 (2.6)

903 (75.0) 20 (1.7) 72 (6.0) 119 (9.9) 83 (6.9) 7 (0.6)

Total Randomized Mean (SD) or Count (%)

Men Mean (SD) or Count (%)

Women Mean (SD) or Count (%)

719 (65.5)

379 (34.5)

280 (25.5) 314 (28.6) 106 (9.7) 177 (16.1) 221 (20.1)

179 (24.9) 216 (30.0) 68 (9.5) 121 (16.8) 135 (18.8)

101 (26.6) 98 (25.9) 38 (10.0) 56 (14.8) 86 (22.7)

51.5 (12.2) 33.3 (8.6) 15.4 (2.6)

51.5 (12.2) 32.2 (7.1) 15.5 (2.6)

51.0 (12.4) 31.3 (6.1)2 15.6 (2.6)1

52.4 (11.7) 34.0 (8.5) 15.3 (2.5)

590 (65.3)4 11 (1.4) 52 (6.8) 59 (7.7) 54 (7.0) 3 (0.4)

313 (34.7) 9 (2.1) 20 (4.6) 60 (13.8) 29 (6.7) 4 (0.9)

835 (76.0) 18 (1.6) 61 (5.6) 103 (9.4) 76 (6.9) 5 (0.5)

553 (76.9)4 10 (1.4) 47 (6.5) 54 (7.5) 52 (7.2) 3 (0.4)

282 (74.4) 8 (2.1) 14 (3.7) 49 (12.9) 24 (6.3) 2 (0.5)

695 (57.7) 297 (24.7) 181 (15.0) 31 (2.6)

505 (65.7)3 174 (22.6) 87 (11.3) 3 (0.4)

190 (43.7) 123 (28.3) 94 (21.6) 28 (6.4)

634 (57.7) 262 (23.9) 171 (15.6) 31 (2.8)

475 (66.1)3 158 (22.0) 83 (11.5) 3 (0.4)

159 (42.0) 104 (27.4) 88 (23.2) 28 (7.4)

152 (12.7)

107 (13.9)

45 (10.3)

136 (12.5)

98 (13.7)

38 (10.1)

161 (13.4) 3.0 (4.6)

134 (17.7)2 3.7 (5.0)

27 (6.2) 1.8 (3.3)

154 (14.2) 3.1 (4.7)

130 (18.3)2 3.7 (5.1)2

24 (6.4) 1.8 (3.4)

555 (46.1) 17.8 (15.7)

375 (48.8)2 18.8 (16.2)

180 (41.4) 15.9 (14.7)

510 (47.3) 17.8 (15.5)

351 (49.9)1 18.9 (16.2)2

159 (42.3) 15.8 (14.0)

6.88 (1.25) 7.57 (1.44)

6.84 (1.19) 7.56 (1.37)

6.95 (1.33) 7.61 (1.57)

6.87 (1.21) 7.56 (1.42)

6.85 (1.17) 7.55 (1.34)

6.90 (1.30) 7.59 (1.55)

1204

1098

P < 0.05 Men vs. Women; 2P < 0.01 Men vs. Women; 3P < 0.01 Difference in proportions in Marital Status between genders; 4P < 0.01 Difference in proportions in Ethnicity between genders. 1

an average of approximately 15.5 years of education. There were few gender differences, although women on average had a higher body mass index (BMI), and in comparison to men were less likely to be married, or to consume alcohol or caffeinated beverages. In addition, Black women were more likely to be participants than Black men. Addition of the 206 participants who were not randomized did not change the overall demographics of the baseline cohort. Baseline neurocognitive measures stratified by gender are shown in Table 1. There were no differences between the cohort that included all 1204 participants who had a baseline polysomnogram and the cohort limited only to the 1098 who were SLEEP, Vol. 34, No. 3, 2011

randomized. Thus, data from only the former are shown. It is notable that overall, the participants had above average intelligence as reflected in their WASI scores, and that men scored significantly higher on the WASI-Full and WASI-Perf as well as both components of the WASI-Perf. Men also performed better on both PVT variables and the PASAT. In contrast, women scored better on the BSRT. Women also were slightly sleepier and scored higher on the HAM-D. Displayed in Table 3 are the baseline polysomnographic data stratified by gender. Except for more extreme values for the respiratory variables, data from the cohort with 1204 participants was not different than the one that was limited only to the 307


Bivariate relationships between neurocognitive measures and demographic factors (data Total Men Women not shown) generally found strong and conMean (SD) Mean (SD) Mean (SD) sistent associations with years of education; Sleep Architecture greater amounts of education corresponding Total Recording Time (min) 500.5 (40.4) 499.8 (38.0) 501.6 (44.4) with better performance. Less consistent, but Total Sleep Time (TST, min) 377.8 (67.6) 376.8 (67.7) 379.6 (67.4) in many cases highly significant were associations with race (Non-Hispanic Whites with Sleep Efficiency (%) 78.4 (13.0) 78.3 (13.2) 78.7 (12.3) better performance than Other Ethnicity), Sleep Latency (min) 19.2 (22.8) 17.3 (20.8)2 22.7 (25.6) gender (men with better performance), and REM Latency (min) 137.8 (82.2) 134.1 (80.5)1 144.3 (84.7) age (better or worse performance depending Wake After Sleep Onset (min) 85.0 (52.9) 87.5 (54.7)1 80.5 (49.2) on test instrument). Mood as reflected by the Stage 1 (%TST) 18.5 (14.5) 20.0 (15.6)2 15.9 (12.0) HAM-D score also impacted performance on Stage 2 (% TST) 60.7 (13.6) 59.7 (14.7)2 62.3 (11.1) other neurocognitive measures with higher Stage 3 (% TST) 2.6 (4.8) 2.1 (4.5)2 3.3 (5.4) scores associated with worse performance 2 Stage 4 (% TST) 0.6 (2.2) 0.4 (1.8) 0,9 (2.7) (data not shown). In contrast, the effect of Stage REM (% TST) 17.6 (7.1) 17.6 (7.1) 17.5 (7.1) sleepiness and alterations in sleep architecture Respiratory Indices were inconsistent with the strongest bivariApnea Hypopnea Index (AHI, events/h TST) 38.2 (26.7) 40.8 (26.7) 33.5 (26.1)2 ate associations found with total sleep time AHI < 104 92 (7.6) 38 (4.9) 54 (12.4) (lower amounts with worse performance), 10 < AHI ≤ 154 144 (12.0) 81 (10.5) 63 (14.5) sleep latency (longer latency with worse per15 < AHI ≤ 304 345 (28.7) 224 (29.1) 121 (27.8) formance), and percent Stage 1 sleep (higher 30 < AHI ≤ 504 285 (23.7) 180 (23.4) 105 (24.1) percent with worse performance). 50 < AHI ≤ 754 204 (16.9) 145 (18.9) 59 (13.6) In Table 4 are displayed the correlation coAHI > 754 134 (11.1) 101 (13.1) 33 (7.6) efficients between respiratory variables and Central Apnea Index (events/h TST) 1.1 (4.3) 1.4 (4.0) 0.6 (4.9)2 neurocognitive measures from the 60% random sample used as the exploratory dataset. As can Minimum Oxygen Saturation (%) 81.2 (8.8) 81.0 (8.6) 81.6 (9.0) be observed, there are consistent but weak asO2 Saturation < 85% (% TST) 2.6 (8.1) 3.2 (9.2) 1.6 (5.5)2 sociations between the AHI and desaturation Oxygen Desaturation Index (events/h TST) 25.5 (25.1) 27.3 (26.0) 22.3 (23.3)2 indices, and the WASI-Full, WASI-Verbal, and Sleep Fragmentation PASAT. There also were some inconsistent and 2 Arousal Index (arousals/h TST) 28.9 (21.0) 30.9 (22.1) 25.4 (18.2) weak correlations between the AHI and de1 Periodic Leg Movement Index (events/h TST) 6.7 (15.6) 7.4 (16.0) 5.5 (14.8) saturation indices, and a few of the other neurocognitive measures, most notably the 2 PVT 1 2 3 P < 0.05 Men vs. Women; P < 0.01 Men vs. Women; N = 1204 except for Stage REM indicators and the ESS. The highest correlation (N = 1194, 10 participants without REM sleep) and Minimum Oxygen Saturation (N = 1202, coefficient noted was 0.266 between the Log 2 participants with missing data); 4 Data represent N (% of N). PVT Mean and O2 Saturation < 85%. Of particular note is the absence of associations be1098 who were randomized. Thus, the table shows only sumtween any of the respiratory variables and the WASI-Perf and mary data from former group. In comparison to recently pubthe Pathfinder. lished normative data from a general population, sleep quality Table 5 shows the final multivariate models for the neurowas suboptimal with moderately reduced sleep efficiency, incognitive variables computed from the 40% of the cohort recreased percent stages 1 and 2 sleep, increased arousal index, served for the validation dataset. For every measure except for and correspondingly decreased stages 3, 4, and REM sleep.40 the BSRT, ESS, and the 2 reaction time (PVT) indicators, years Sleep and REM latencies were longer in women. Women also of education was the strongest predictor of performance. For had less percent stage 1 and greater percent stages 3 and 4 the WASI measures, race other than Non-Hispanic White was sleep. With respect to respiratory variables, the mean AHI in a consistent negative impact factor on performance as well. all participants of 38.2/h was indicative of relatively severe However, the amount of variance explained by these models OSA with greater severity in men than women. Additionally, was modest with r2 ranging from 0.039 to 0.296. Furthermore, 28% of all participants had an AHI > 50/h. The O2 Saturation the impact of respiratory and sleep variables was quite lim< 85% and the desaturation index, but not the minimum O2 ited. For the 2 primary outcome variables analyzed, % Stage saturation, were more severe in men as well. The central ap1 Sleep negatively impacted performance on the Pathfinder nea index was quite low, suggesting that almost all apneic and Test, but there was no effect from any other respiratory or hypopneic events were obstructive. There were no significant sleep variable. For secondary outcomes, statistically significorrelations between age and AHI (r = 0.039, P = 0.171) or cant contributions by oxygen desaturation indices to poorer oxygen desaturation index (r = −0.008, P = 0.789). However, performance were found on the WASI-Block Design, ESS, weak negative correlations were noted between age and O2 PVT Mean, and the PASAT. Borderline statistical significance Saturation < 85% (r = −0.081, P = 0.005) and Minimum O2 was noted for WASI-Vocab and WASI-Perf. Overall AHI was Saturation (r = −0.071, P = 0.014). not related to neurocognition on any outcomes (For outcomes Table 3—Baseline polysomnographic data for all participants3 stratified by gender

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without significant associations, data shown are with desaturation indices). However, the contribution of either AHI or oxygen desaturation to the overall variance explained in the models was < 2% in all cases. Of additional interest is that sleepiness assessed by either the ESS or SSS only affected performance on the PVT Median. To determine whether there were associations between high values of AHI and neurocognitive function, comparisons of neurocognitive function were made using only participants with an AHI < 10 events/h or AHI ≥ 30 events/h. No significant associations were observed (data not shown). This analysis was repeated using only participants with an AHI < 10 events/h or AHI ≥ 50 events/h. Performance on the Pathfinder Test and the BSRT was worse for those with an AHI ≥ 50 events/h on bivariate analyses (Pathfinder: 22.8 ± 0.9 vs. 25.0 ± 0.5 sec, P = 0.03; BSRT: 52.1 ± 1.5 vs. 48.6 ± 0.6 words correct, P = 0.03). However, these findings were no longer significant after multivariate analyses. A similar analysis was performed to determine if there was an impact of severe oxygen desaturation. For this analysis, only participants who met one of the 2 following criteria were used. Those who had 2% or more of their PSG total sleep time less than 85% were classified as severe oxygen desaturation (Severe Desaturation) and those who never had any PSG saturation less than 90% were considered as having minimal or no desaturation (No Desaturation). As can be shown in Table 6, performance on the WASI-Full, WASI-Perf, WASI-BD, WASIMATR, and PVT Mean Reaction Time was negatively impacted by severe oxygen desaturation. Slight trends for worse performance also were noted for WASI-Verbal, WASI-Simil, PVT Median Reaction Time, and PASAT (data not shown, all 0.10 < P < 0.20). To investigate whether those in the severe oxygen desaturation group had chronic lung disease, the prevalence of asthma and chronic obstructive lung disease was compared between the Severe Desaturation and No Desaturation groups. No differences in prevalence were observed although the number with these conditions was small. However, waking oxygen saturations were lower in the Severe Desaturation group (96.2% ± 1.1% vs. 92.1% ± 2.4%, P < 0.001), and BMI was higher (38.8 ± 8.2 vs. 27.4 ± 4.3 kg/m2, P < 0.001). Furthermore, 10 of those in the Severe Desaturation group had waking oxygen saturations below 90%.

Table 4—Correlation between neurocognitive and sleep disordered breathing measures (N = 722)1 Neurocognitive Measures2 AHI WASI Full r -0.100 p 0.008 n 711 WASI Verbal r -0.122 p 0.001 n 712 WASI Vocabulary r -0.108 p 0.004 n 712 WASI Similarities r -0.113 p 0.003 n 712 WASI Performance r -0.047 p 0.210 n 711 WASI Block Design r -0.028 p 0.462 n 712 WASI Matrix Reasoning r -0.056 p 0.132 n 711 Pathfinder r 0.043 p 0.252 n 713 BSRT r -0.104 p 0.005 n 713 LOG PVT Median r 0.028 p 0.464 n 706 LOG PVT Mean r 0.116 p 0.002 n 706 PASAT r -0.100 p 0.008 n 703 ESS r 0.128 p 0.001 n 722

DISCUSSION In this study using a large cohort of participants entering a randomized study of the impact of long-term CPAP on neurocognitive functioning, cross-sectional analysis of the associations between indices of sleep quality and OSA, and various measures of neurocognitive performance showed only weak and inconsistent relationships at baseline. Sleep quality as assessed by laboratory polysomnography had relatively little relationship with neurocognitive performance. Although respiratory indices of OSA severity appeared to be more associated with worse neurocognitive function than sleep quality indicators, their effect still was quite modest overall. Nevertheless, there was some evidence that oxygen desaturation negatively correlated with performance to a slight degree on a broad range of neurocognitive measures. This was particularly evident for those participants with severe oxygen desaturation (i.e., desaturation < 85%). SLEEP, Vol. 34, No. 3, 2011

Sleep Disordered Breathing Measures Minimum % TST < 85% Desaturation SpO2 Saturation Index 0.123 0.001 710

-0.062 0.099 711

-0.130 < 0.001 711

-0.128 0.001 711

-0.075 0.046 712

-0.150 < 0.001 712

0.126 0.001 711

-0.068 0.069 712

-0.137 < 0.001 712

0.102 0.007 711

-0.063 0.095 712

-0.134 < 0.001 712

0.08 0.033 710

-0.033 0.385 711

-0.078 0.037 711

0.085 0.024 711

-0.004 0.916 712

-0.043 0.255 712

0.040 0.290 710

-0.039 0.304 711

-0.092 0.014 711

-0.049 0.188 712

-0.031 0.404 713

0.021 0.575 713

0.094 0.012 712

-0.024 0.524 713

-0.079 0.035 713

-0.036 0.335 705

0.112 0.003 706

0.069 0.065 706

-0.126 0.001 705

0.266 < 0.001 706

0.163 < 0.001 706

0.141 < 0.001 702

-0.084 0.027 703

-0.110 0.004 702

-0.086 0.022 721

0.187 < 0.001 722

0.118 0.001 722

Analyses performed on the 60% exploratory dataset; 2Abbreviations of neurocognitive measures defined in the text. 1

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We observed that increased % Stage 1 Table 5—Regression models for factors associated with neurocognition (N = 4829) sleep was weakly associated with poorer Partial η performance on the Pathfinder test. The 6 7 8 Factor B SE 95% CI Squared P Pathfinder assesses attention and psychoLower Upper motor function. Although the magnitude WASI Full of the association was modest, this finding Years Education 2.203 0.220 1.861 2.725 0.190 < 0.01 suggests that diminished sleep quality in 1 Race -8.393 1.340 -11.026 -5.759 0.078 < 0.01 those with OSA contributes to the diffiAHI -0.034 0.220 -0.077 0.010 0.005 0.13 culty in maintaining attention and concen2 Adjusted r = 0.279 tration often observed in these patients. To WASI Verbal our knowledge, there have been no previYears Education 2.422 0.218 1.994 2.850 0.211 < 0.01 ous reports of objectively measured sleep Race1 -7.904 1.350 -10.560 -5.250 0.069 < 0.01 quality negatively impacting performance AHI -0.024 0.022 -0.067 0.019 0.003 0.27 on either of the Trail Making tasks. HowAdjusted r2 = 0.296 ever, some, but not all previous studies WASI Vocabulary have found a relationship between sleep Years Education 1.640 0.160 1.326 1.953 0.186 < 0.00 restriction or deprivation and poorer perRace1 -6.117 0.980 -8.040 -4.190 0.078 < 0.00 formance on Trail Making.41 Our results Desaturation Index -0.033 0.017 -0.066 0.001 0.008 0.06 Adjusted r2 = 0.280 would be consistent with those studies finding such a negative relationship. WASI Similarities Years Education 1.278 0.129 1.023 1.532 0.174 < 0.00 Notwithstanding the stage 1 sleep Path1 Race -4.132 0.804 -5.710 -2.550 0.054 < 0.00 finder correlation, overall sleep quality and Desaturation Index -0.012 0.014 -0.039 0.015 0.002 0.38 sleep duration had little relationship with 2 Adjusted r = 0.248 neurocognitive function. Although sleep WASI Performance deprivation negatively affects neurocogniYears Education 1.600 0.238 1.132 2.068 0.089 < 0.01 tive performance on a variety of domains Race1 -6.910 1.454 -9.769 -4.054 0.046 < 0.01 including learning, executive function and Desaturation Index -0.043 0.026 -0.094 0.007 0.006 0.09 vigilance,42 the disturbances in sleep archiAdjusted r2 = 0.154 tecture and duration observed in the cohort WASI Block Design as a whole were relatively mild, and were Years Education 0.852 0.156 0.545 1.158 0.056 < 0.01 Race1 -7.370 1.932 -11.170 -3.570 0.033 < 0.01 likely insufficient to result in a demon2 Gender 5.961 2.369 1.423 10.499 0.020 0.01 strable effect on the measures used in the 5 Marital Status 5.159 2.521 0.201 10.113 0.013 0.04 study. Minimum SpO 0.141 0.051 0.041 0.240 0.017 0.01 2 In contrast to the relative lack of associAdjusted r2 = 0.163 ation between sleep quality and sleep duraWASI Matrix Reasoning tion, and neurocognitive performance, we Years Education 0.959 0.151 0.662 1.255 0.080 < 0.01 found consistent, albeit weak associations Race1 -4.430 0.921 -6.240 -2.620 0.047 < 0.01 between several indices of oxygen desatuAHI -0.200 0.015 -0.050 0.010 0.004 0.19 ration and results from WASI-Block DeAdjusted r2 = 0.143 sign, PVT Mean, the ESS and the PASAT. 1 Comparison is Non-Hispanic White (Reference Group) vs. Other Ethnicity/Race; 2Reference group As reviewed by Beebe and colleagues,17 is Women; 3 PVT Median Reaction Time was log transformed, and coefficients are expressed as most studies have not found that OSA afchange in log seconds per unit change in the independent variable; 4PVT Mean Reaction Time fects overall intelligence and verbal abiliwas log transformed, and coefficients are expressed as change in log seconds per unit change ties. While our failure to demonstrate any in the independent variable; 5Reference group is Not Married; 6Estimated regression coefficient; 7 associations with OSA severity on the WAEstimated standard error; 8Partial eta squared is an estimate of effect size; 9Result computed from SI-Full, WASI-Verbal, and WASI-Perf are 40% validation sample. Table 5 continues on the following page consistent with these previous studies, the trend towards poorer performance on the WASI-Vocab does suggest that OSA can negatively affect perevident neurocognitive impairment. In addition, recent studies formance on these domains to a small degree. The preponderhave indicated that the brain attempts to compensate to avoid ance of previous studies, however, indicate that OSA impairs decrements in performance in the setting of untreated OSA.43,44 performance on visual ability, executive function, motor speed, It is possible that in a population of previously untreated indiand vigilance. Our finding that performance on the PVT and viduals, compensatory mechanisms partially masked neurocogPASAT was diminished is consistent with these previous obsernitive impairment. Nevertheless, the small effect observed is vations although their overall contribution in relation to other consistent with results from another large general population factors such as previous education and ethnicity was small. cohort.20 Most previous studies of the impact of OSA on neurocogniAnother perspective on the strength of the associations found tive function have utilized participants recruited from clinical in this study can be found by examining the effect sizes desettings, and thus may have selected those who had clinically rived from the multivariate analyses. As shown in Table 5, the SLEEP, Vol. 34, No. 3, 2011

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relatively severe oxygen desaturation was predictive of worse performance on sevPartial η eral of our measures. In contrast, there Factor B6 SE7 95% CI Squared8 P were no significant associations with Lower Upper AHI in our adjusted models. Similar findPathfinder ings have been noted by others in large Years Education -0.307 0.102 -0.508 -0.106 0.019 < 0.01 population cohorts.22,23 Not surprisingly, % Stage 1 Sleep 0.063 0.024 0.017 0.109 0.015 0.02 as we observed, relatively severe oxygen Age 0.234 0.021 0.192 0.276 0.208 < 0.01 desaturation during a PSG is associated AHI 0.005 0.011 -0.017 0.028 0.000 0.63 with lower waking oxygen saturations. 2 Adjusted r = 0.245 In addition, these subjects had a higher BSRT BMI. Therefore, it is possible that obesity Age -0.235 0.033 -0.299 0.170 0.099 < 0.01 hypoventilation syndrome was present as Gender2 -3.227 1.639 -6.447 -0.007 0.008 < 0.05 well as obstructive sleep apnea, and inYears Education 0.779 0.153 0.478 1.080 0.053 < 0.01 Race1 4.949 1.438 2.123 7.776 0.025 < 0.01 creased the risk of worse neurocognitive Minimum SpO2 0.019 0.052 -0.083 0.121 0.000 0.72 performance. Because arterial blood gases Adjusted r2 = 0.180 were not measured as part of this study, we PVT Median Reaction Time3 could not determine whether any of our Age < 0.000 < 0.000 < 0.000 0.001 0.008 0.05 subjects were hypoventilating. It is posStanford Sleepiness Scale 0.007 0.003 0.002 0.012 0.014 0.01 sible that the strength of the associations 2 Gender -0.022 0.005 -0.032 -0.012 0.039 < 0.01 we found are underestimated because Desaturation Index < 0.000 < 0.000 < 0.000 < 0.000 0.000 0.75 those with very severe oxygen desaturaAdjusted r2 = 0.065 tion were excluded. Nevertheless, taken as PVT Mean Reaction Time4 a whole, our data indicate that decrements %TST < 85% Saturation 0.004 0.001 0.002 0.007 — < 0.00 in neurocognitive performance related to Adjusted r2 = 0.039 PASAT OSA are predominantly a result of hypoxYears Education 3.606 0.718 2.196 5.016 0.058 < 0.01 emia, rather than the frequency of sleep Age -1.215 0.156 -1.522 -0.909 0.121 < 0.01 disordered breathing events or reductions Minimum SpO2 0.536 0.243 0.058 1.014 0.009 0.03 in sleep quality. Our results are consistent 1 Race -14.730 6.709 -27.916 -1.545 0.015 0.03 with those reported from the Sleep Heart 2 Adjusted r = 0.185 Health Study,20 as well as intermittent hyEpworth Sleepiness Scale poxia models of sleep disordered breathing HamD Total Score 0.130 0.046 0.040 0.220 0.017 < 0.01 in experimental animals.47 Alternatively, it Minimum SpO2 -0.061 0.023 -0.107 -0.016 0.015 < 0.01 has been suggested by others that sleepiTotal Sleep Time 0.007 0.003 0.001 0.012 0.012 0.02 ness, most likely caused by sleep fragAdjusted r2 = 0.048 mentation, is the mechanism underlying 1 neurocognitive dysfunction in OSA.48 This Comparison is Non-Hispanic White (Reference Group) vs. Other Ethnicity/Race; 2Reference group is Women; 3 PVT Median Reaction Time was log transformed, and coefficients are expressed as was not supported by our results. change in log seconds per unit change in the independent variable; 4PVT Mean Reaction Time The most powerful factor explaining was log transformed, and coefficients are expressed as change in log seconds per unit change better neurocognitive performance in our in the independent variable; 5Reference group is Not Married; 6Estimated regression coefficient; study was educational level. Non-Hispanic 7 8 9 Estimated standard error; Partial eta squared is an estimate of effect size; Result computed from White ethnicity was an important positive 40% validation sample. predictor on many measures as well. These findings are not surprising given the large partial η squared values for % Stage 1 on the Pathfinder Test, amount of data demonstrating a correlation between intelligence Minimum SpO2 on the PASAT and ESS were 0.015, 0.009, and testing and educational attainment as well as poorer perfor0.012, respectively. Partial η squared is a marker of effect size, mance by many minority groups on standardized intelligence and values of approximately 0.01 are considered small.45 In tests. Although there were some gender differences in neurocogcontrast, in one recent study, the impact of obesity on risk of nitive performance when the data were unadjusted, multivariate hypertension was found to have a medium effect size.46 analyses found that gender was not an important factor on most Mechanisms most commonly invoked to explain the assoneurocognitive measures, and have not been found to be imporciation between OSA and neurocognition are the negative eftant in previous studies in large populations. fects of sleep disordered breathing events on sleep continuity There are several limitations and caveats to our results. First, and/or the impact of repetitive hypoxemic events. In this study, although we studied a large cohort of participants, the analysis is oxygen desaturation indices explained virtually all of the obcross-sectional. Thus, causation cannot be unequivocally demserved associations between OSA severity and neurocognitive onstrated. Second, inasmuch as the data utilized were collected performance. Furthermore, when we restricted analysis only as part of the baseline visit for a randomized controlled trial of to those with severe OSA (AHI ≥ 30 or ≥ 50), we found no therapeutic vs. sub-therapeutic CPAP in OSA individuals, viror few associations on bivariate analyses, but did observe that tually all of the participants in the cohort had some degree of Table 5 (continued)—Regression models for factors associated with neurocognition (N = 4829)

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pants in our study were recruited both from clinical venues as well as from the general Partial η population through advertisement. IndiFactor B6 SE7 95% CI Squared8 P viduals in the latter category may have had Lower Upper fewer symptoms, and thus have had less WASI Full neurocognitive impact from their OSA. Race1 -7.350 2.374 -12.047 -2.653 0.070 0.002 Unfortunately, recruitment source was not Years Education 2.164 0.430 1.314 3.014 0.166 < 0.001 collected as part of the study although it Desaturation3 6.461 2.164 2.180 10.743 0.066 0.003 is estimated that 70% were recruited from 2 Adjusted r = 0.287 the general population. Sixth, although the WASI Performance mean AHI in this study was 38.2/hour, hyRace1 -7.557 2.547 -12.598 -2.516 0.065 0.004 popneas were identified if there was a decYears Education 1.535 0.461 0.623 2.448 0.080 0.001 rement in nasal pressure, and an associated Desaturation3 7.828 2.322 3.233 12.423 0.082 0.001 > 3% oxygen desaturation or an arousal. Adjusted r2 = 0.220 WASI Block Design In contrast, the Sleep Heart Health Study Race1 -5.071 1.678 -8.390 -1.751 0.068 0.003 used a thermistor and allowed only associYears Education 0.902 0.302 0.305 1.499 0.066 0.003 ated 4% oxygen desaturations to identify Desaturation3 4.340 1.530 1.310 7.366 0.060 0.005 hypopneas.4,5 Thus, the severity of OSA in Gender 4.527 1.472 1.613 7.440 0.070 0.003 our cohort may have been less than in other Marital Status4 3.176 1.455 0.296 6.055 0.036 0.031 studies. Last, the variance explained by all 2 Adjusted r = 0.260 of the variables included our models was WASI Matrix Reasoning relatively small. This suggests a number Race1 -3.473 1.683 -6.803 -0.143 0.041 0.032 of other factors not included in our study Years Education 0.993 0.305 0.390 1.595 0.077 0.001 are important in explaining neurocognitive Desaturation3 4.558 1.534 1.523 7.594 0.065 0.004 Adjusted r2 = 0.173 performance in the setting of OSA. PVT Mean Reaction Time5 In summary, in a large cohort of individDesaturation3 0.073 0.030 0.013 0.132 0.000 0.017 uals with OSA recruited for a large randomAdjusted r2 = 0.043 ized controlled intervention trial of CPAP, associations between severity of OSA as 1 Comparison is Non-Hispanic White (Reference Group) vs. Other Ethnicity/Race; 2Reference group well as objectively determined sleep quality 3 4 is Women; Reference group is ≥ 2% of total sleep time with oxygen saturation < 85%; Reference and duration, and neurocognitive function 5 group is Not Married; PVT Mean Reaction Time was log transformed, and coefficients are expressed were weak and inconsistent. When impairas change in log seconds per unit change in the independent variable; 6Estimated regression ment was observed, oxygen desaturation coefficient; 7Estimated standard error; 8Partial eta squared is an estimate of effect size; 9N = 47 rather than the number of sleep-disordered (minimal or no desaturation); N = 83 (severe desaturation); See text for definitions. breathing events affected neurocognitive performance. These findings indicate that OSA. Therefore, there was a paucity of participants who did not the relative impact of OSA on neurocognition may be minor in have any OSA. If neurocognitive impairment in OSA is more most individuals with this condition. of a threshold rather than a “dose-response” type of effect, it is possible that our inability to demonstrate strong associations ACKNOWLEDGMENTS between OSA severity and neurocognition may be explained APPLES was funded by HL068060 from the National Heart, by the lack of an adequate comparison group. Third, our study Lung and Blood Institute. The APPLES pilot studies were suppopulation was relatively well educated and had above average ported by grants from the American Academy of Sleep Medicine intelligence. There is some suggestion that persons with higher and the Sleep Medicine Education and Research Foundation to levels of intelligence may be more resistant to any adverse imStanford University and by the National Institute of Neurologipact of OSA on neurocognition.49 Fourth, reviews of the relacal Disorders and Stroke (N44NS002394) to SAM Technology. tionship between OSA and neurocognitive function indicate that In addition, APPLES investigators gratefully recognize the executive function is one domain that is frequently impaired in vital input and support of Dr. Sylvan Green who died before the those with OSA.17,50 Although one of our primary outcome mearesults of this trial were analyzed, but was instrumental in its sures, the SWMT is sensitive to changes in executive function, design and conduct. it was not designed to be used in cross-sectional analysis, and thus not included in this analysis. Furthermore, our neurocogAdministrative Core nitive test battery, while comprehensive, did not utilize every Clete A. Kushida, MD, PhD; Deborah A. Nichols, MS; Eileen measure previously shown to be impacted by OSA. Moreover, B. Leary, BA, RPSGT; Pamela R. Hyde, MA; Tyson H. Holmes, due to limitations in the time allowed for testing it was not posPhD; Daniel A. Bloch, PhD; William C. Dement, MD, PhD sible to conduct a long duration vigilance task (e.g., a 14-20 minute continuous performance test). Thus, it is possible that Data Coordinating Center the associations between OSA severity and neurocognitive Daniel A. Bloch, PhD; Tyson H. Holmes, PhD; Deborah function may be stronger than we have observed. Fifth, particiA. Nichols, MS; Rik Jadrnicek, Microflow; Ric Miller, Table 6—Regression models for factors associated with severe oxygen desaturation9

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Microflow; Usman Aijaz, MS; Aamir Farooq, PhD; Darryl Thomander, PhD; Chia-Yu Cardell, RPSGT; Emily Kees; Michael E. Sorel, MPH; Oscar Carrillo RPSGT; Tami Crabtree, MS; Ray Balise, PhD; Tracy Kuo, PhD

from Pfizer, Merck, Somaxon, Evotec, Actelion, Vanda, Neurogen, Sanofi-Aventis, Ventus Medical, Respironics, and Jazz. He has consulted for Pfizer, Sanofi-Aventis, Cephalon, Schering-Plough/Organon, Neurocrine, Takeda, Actelion, Sepracor, Jazz, Respironics, Transcept, Neurogen, GlaxoSmithKline, Somaxon, Eli Lilly, Evotec, Merck, Kingsdown, Vanda, Ventus Medical, and Somnus. Dr. Schweitzer has been the principal investigator by studies sponsored through grants to his institution from Neurogen, Pfizer, Merck, Somnus, and Ventus Medical. Dr. Simon has received research support from Ventus Medical and has participated in speaking engagements for Asante Communications. Dr. Kay has received research support from Cephalon and Merck; he is a 50% owner of CogScreen, which provided licenses and tests to the APPLES study at cost. Dr. Dement has participated in paid speaking engagements. Dr. Kushida Has received research support through grants to Stanford University from Ventus Medical, Merck, Respironics, Jazz, Cephalon, GlaxoSmithKline, Pacific Medico, and Xenoport. Dr. Hirshkowitz has participated in speaking engagements for Cephalon and Takeda and has consulted for Cephalon and Sanofi-Aventis.

Clinical Coordinating Center Clete A. Kushida, MD, PhD; William C. Dement, MD, PhD; Pamela R. Hyde, MA; Rhonda M. Wong, BA; Pete Silva; Max Hirshkowitz, PhD; Alan Gevins, DSc; Gary Kay, PhD; Linda K. McEvoy, PhD; Cynthia S. Chan, BS; Sylvan Green, MD Clinical Centers Stanford University

Christian Guilleminault, MD; Eileen B. Leary, BA, RPSGT; David Claman, MD; Stephen Brooks, MD; Julianne Blythe, PA-C, RPSGT; Jennifer Blair, BA; Pam Simi; Ronelle Broussard, BA; Emily Greenberg, MPH; Bethany Franklin, MS; Amirah Khouzam, MA; Sanjana Behari Black, BS, RPSGT; Viola Arias, RPSGT; Romelyn Delos Santos, BS; Tara Tanaka, PhD

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Stuart F. Quan, MD; James L. Goodwin, PhD; Wei Shen, MD; Phillip Eichling, MD; Rohit Budhiraja, MD; Charles Wynstra, MBA; Cathy Ward; Colleen Dunn, BS; Terry Smith, BS; Dane Holderman; Michael Robinson, BS; Osmara Molina, BS; Aaron Ostrovsky; Jesus Wences; Sean Priefert; Julia Rogers, BS; Megan Ruiter, BS; Leslie Crosby, BS, RN St. Mary Medical Center

Richard D. Simon Jr, MD; Kevin Hurlburt, RPSGT; Michael Bernstein, MD; Timothy Davidson, MD; Jeannine Orock-Takele, RPSGT; Shelly Rubin, MA; Phillip Smith, RPSGT; Erica Roth, RPSGT; Julie Flaa, RPSGT; Jennifer Blair, BA; Jennifer Schwartz, BA; Anna Simon, BA; Amber Randall, BA St. Luke’s Hospital

James K. Walsh, PhD; Paula K. Schweitzer, PhD; Anup Katyal, MD; Rhody Eisenstein, MD; Stephen Feren, MD; Nancy Cline; Dena Robertson, RN; Sheri Compton, RN; Susan Greene; Kara Griffin, MS; Janine Hall, PhD Brigham and Women’s Hospital

Daniel J. Gottlieb, MD, MPH; David P. White, MD; Denise Clarke, BSc, RPSGT; Kevin Moore, BA; Grace Brown, BA; Paige Hardy, MS; Kerry Eudy, PhD; Lawrence Epstein, MD; Sanjay Patel, MD Sleep HealthCenters

For the use of their clinical facilities to conduct this research. DISCLOSURE STATMENT Respironics, Inc. supplied the CPAP and sham CPAP devices for this study. There was no other industry support. Dr. Walsh has received research support through grants to his institution SLEEP, Vol. 34, No. 3, 2011

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Appendix 1—Neurocognitive testing schedule TIME NNC Session 1 9:30–10:00 am 10:00–10:25 am 10:25–10:50 am 10:50–11:05 am 11:05–11:35 am 11:35–11:40 am Break (20- in lab) SNC Session 2 12:00–12:25 pm 12:25–12:50 pm Lunch Break (25) 1:15–1:50 pm Break (10- in lab) SNC Session 3 2:00–2:25 pm 2:25–2:50 pm 2:50–3:10 pm 3:10–3:25 pm 3:25–3:45 pm Break (15- in lab) SNC Session 4 4:00–4:25 pm 4:25–4:30 pm 4:30–4:45 pm

Other

MWT

Neurocognitive Test Battery SWMT

BSRT

SDC/DR

PF N/C

VSC

SAT

X

X

X

X

PVT

PASAT

Qs X X X Psych 1 recall

X X

X X SAQLI X X

X SIs Psych 2

Other: Qs = various self-administered questionnaires (BDI, POMS, QWB-SA. ESS); Psych 1 = administration of Hamilton Rating Scale for Depression and Mini International Neuropsychiatric Interview modules; SAQLI = Calgary Sleep Apnea Quality of Life Index; Sis = Administration of standardized instructions to subject; Psych 2 = finish administration of psychological interviews if not completed during Psych 1; MWT = maintenance of wakefulness test; SWMT = Sustained Working Memory Test; BSRT = Buschke Verbal Selective Reminding Test (plus 30-min recall); SDC/DR = Symbol Digit Coding (plus 20-30-min recall [SDCDR]); PF N/C = Pathfinder Number/ Pathfinder Combined; VSC = Visual Sequence Comparison; SAT = Shifting Attention Test; PVT = Psychomotor Vigilance Task; PASAT = Paced Auditory Serial Addition Test. All CogScreen tests are administered between 1:15–1:50 pm as one computerized module (SDC, SDCDR, PF N/C, VSC, and SAT). Each subject has 70 minutes of “break time” incorporated into his or her day of neurocognitive testing.

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Appendix 2—Additional assessments and measures included in APPLES Tests of Attention and Psychomotor Function • Symbol Digit Coding (CogScreen computer analogue of the Digit Symbol Substitution Test) • Visual Sequence Comparison (Component of APPLES CogScreen package) • Shifting Attention Test Instruction Condition (Component of APPLES CogScreen package) Tests of Learning and Memory • Symbol Digit Coding Delayed Recall Task Tests of Executive and Frontal-Lobe Function • Pathfinder Combined (CogScreen computer analogue of Trails Making B) • Shifting Attention Test Discovery Condition (Component of APPLES CogScreen package) Psychological Mood and Quality of Life Assessment • Profile of Mood States • Beck Depression Inventory • Mini International Neuropsychiatric Interview • Hamilton Rating Scale for Depression • Calgary Sleep Apnea Quality of Life Index • Quality of Well-Being Scale, Self-Administered Sleep Assessments • Fatigue Scale: Levels of Alertness • Morning Questionnaire • Bedtime Questionnaire • Morningness-Eveningness Questionnaire (Derived from Horne and Ostberg) • Sleep Habits Questionnaire (Modified from the Sleep Heart Health Study) • Sleep Log Other Measures (On Initial Screening Only) • Clinical Screening Questionnaire • Mini Mental State Examination • Judgement of Line Orientation

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